| 计及需求响应的含风电场多目标低碳经济调度 |
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| 引用本文： | 宋云东,周志强,应 勇,张远博,刘 旭. 计及需求响应的含风电场多目标低碳经济调度[J]. 现代电力, 2016, 33(6): 7-13 |
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| 作者姓名： | 宋云东 周志强 应 勇 张远博 刘 旭 |
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| 作者单位： | 1.辽宁省电力有限公司电力科学研究院,辽宁沈阳 110006; |
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| 摘 要： | 综合考虑发电成本、碳排放量和用户满意度,建立计及需求响应的含风电场多目标低碳经济调度模型。该模型采用随机规划理论描述风电出力的不确定性,并应用风电出力分布函数将其转化为等价的确定性模型;通过优化需求侧资源来调整次日的负荷曲线,以提高系统负荷率和风电消纳能力;引入用户满意度约束,保证调度方案使用户满意;将源荷侧资源整合统一调度来适应大规模风电并网和满足系统节能减排的要求。在人工鱼群算法搜索过程中结合禁忌搜索思想,并引入多目标搜索机制,提出了一种多目标改进鱼群算法对模型求解。采用逼近理想解排序法对帕累托前沿个体排序,辅助决策者确定最佳的调度方案。算例仿真结果验证了所提模型的合理性和算法的有效性。
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| 关 键 词： | 机会约束规划 需求响应 多目标优化 分时电价 用户满意度 低碳经济调度 |
| 收稿时间： | 2015-10-10 |
Multi-objective Low-carbon Economic Dispatching for Power Grid Integrated with Wind Farm by Considering Demand Response |
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| Affiliation: | 1.Electric Power Research Institute Liaoning Electric Power Company Limited, Shenyang 110006, China;3.Liaoning Provincial Electric Power Co. Ltd, Shenyang 110006, China; |
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| Abstract: | By combining the generation cost, carbon emissions and customers satisfaction, the multi-objective and low-carbon economic dispatch model for power grid integrated with wind farm is built by considering demand response. The stochastic programming theory is used in this model to describe the uncertainty of the wind power, and the model is converted to an equivalent deterministic model by using distribution function of wind power output. In addition, the load curve of next day is adjusted by optimizing demand side resources to improve load rate and absorptive capacity of wind power. Furthermore, customers satisfaction constraint is introduced to ensure that the scheduling scheme satisfies customer. And the resources of source and load can be unified coordinated to meet the requirements of the application of large-scale grid-connected wind farm, the energy-saving and emission-reduction. Through introducing tabu search and more targeted search mechanism in searching process of artificial fish swarm algorithm, a multi-objective improved artificial fish swarm algorithm is proposed to solve this model by introducing multi-objective searching mechanism. And by using the technique for order preference by similarity to ideal solution (TOPSIS) to sort the Pareto frontier, the optimal scheduling scheme is determined. In the end, simulation results verify the rationality and validity of the proposed model and algorithm. |
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